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Three papers from today's arXiv: a 32B medical model beats DeepSeek-R1 in rare disease diagnosis, a KV cache method keeps 97% accuracy with 3% memory, and a new benchmark red-teams agentic AI systems.
Three new papers cover 4x KV cache savings for tree reasoning, latent-space jailbreaks that bypass safety on 15 models, and GPT-5.4's 40% ceiling on drug design tasks.
Three papers from today's arXiv: a joint fix for KV cache bloat and attention cost, new evidence that fine-tuning belongs in the middle of a transformer, and why stronger reasoning hurts behavioral simulation.
Three papers this week challenge how we think about MoE expert routing, LLM context management, and the limits of activation steering.
Google Research's TurboQuant compresses LLM key-value cache by 6x and delivers 8x speedup on H100 GPUs with zero accuracy loss - no fine-tuning required.
Today's arXiv picks: a state-machine framework that makes GUI agents 12x cheaper, a training method that forces chain-of-thought to be honest, and a KV cache system that matches full quality at 1% the memory.
